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篇名 貨櫃定期航商珠江三角洲空櫃調度模式之研究—以某國籍航商之個案為例
卷期 42:2
並列篇名 A STUDY ON AN EMPTY CONTAINER DISPATCH MODEL FOR MERCHANT SHIPS IN THE PEARL RIVER DELTA AREA – THE CASE STUDY ON MERCHANT SHIPS OF SPECIFIC NATIONALITY
作者 趙時樑涂智凱
頁次 121-150
關鍵字 珠江三角洲貨櫃調度定期航運網路分析Pearl River DeltaContainer repositioningLiner shippingNetwork analysisTSSCI
出刊日期 201306

中文摘要

珠江三角洲(Pearl River Delta, PRD)是中國經貿活動最繁榮的港口經 濟區之一,其以珠江錦密水系為主之獨特貨櫃運輸系統,使得全球廠商可 以深入内陸設立生產據點,利用低廉勞工與土地成本取得競爭優勢,生產 成品則可透過香港、深圳等國際港口出口至世界主要港口。由於經貿與生 產活動相當活絡,此一具龐大貨櫃運輸需求之市場已成為全球主要定期航 商積極發展之重點。然由於PRD地區獨特的水陸交錯運輸體系,使得其空 櫃調度問題更加複雜。本研究旨在從國籍航商之角度,探討PRD地區空櫃 調度與管理問題,考量重櫃拆空、空櫃調度、貨櫃租賃等因素,以及水、陸運輸系統之特性與限制條件,建立網路研究模式協助分析問題,並以某 國籍航商之個案為例,進行淡旺季貨櫃調度最佳策略之案例研究以及各據 點需求變動時之敏感性分析。

英文摘要

The Pearl River Delta (PRD) demonstrates one of the most prosperous trading activities in harbor economies in China. The unique transportation system of the Pearl River stimulates business around the world to establish inland production facilities in China, subsequently utilizing the cheap labor and land costs of China as a competitive advantage. Finished products can then be shipped worldwide via international harbors located in Hong Kong and Shenzhen. Because of the prevalent trade and production activity, the massive requirement for transportation has led the PRD to become an essential stop for merchant ships worldwide. Furthermore, due to the diversity of transportation modes in the PRD, liner carriers must efficiently handle the complicated problem of container management. Thus, this study proposes a mathematical network model in provision of the empty container management problem in the PRD. Considering numerous factors such as heavy container dismantlement, empty container dispatch, and container rental, as well as the characteristics and limitations of the land and water transportation systems in the PRD, this mathematical network model can be used to effectively analyze problems. Subsequently, by using the merchant ships of specific nationalities as an example, this study analyzed the optimal dispatch strategies during peak and off-peak seasons, and further conducted sensitivity analysis of various locations during demand changes.

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